escriptive Statistics Analysis (PART-A)
Table5.2: Descriptive Statistics of impact of International Financial Reporting Standards (IFRS) Implementation on financial performance in Indian companies (N=40). (Questions from 10 to 28)
Table-5.2
Q.NO. Factors (SA)
(5)
(A)
(4)
(DA)
(3)
(SDA)
(2)
(UD)
(1)
Total Mean SD CV
10 The adoption of IFRS helps improving transparency, comparability and usefulness of accounts to users
34 6 0 0 0 40 4.78 0.42 0.09
11 The adoption of IFRS improves the efficiency of capital market operations
29 11 0 0 0 40 4.75 0.44 0.09
12 IFRS is better than IAS and
IndAS
0 5 25 6 4 40 2.23 1.03 0.46
13 The cost of implementation of
IFRS is high as it requires additional/trained human resources 3 4 27 6 0 40 2.38 1.08 0.45
14 Implementation of IFRS is a*…show more content…*

Financial Statements based on FVA are more transparent than those prepared using HCA 1.000 .708 Q26. FVA will enhance transparency for comparability. 1.000 .738 Q27. FVA limits the company’s ability to manipulate their net income. 1.000 .666 Q28. FVA method is a complex method for financial reporting. 1.000 .724 Extraction Method: Principal Component Analysis. Conclusion: In the above table if the extraction value is more one can say that most of the respondents are agreeing with that factor. Table-5.4 Total Variance Explained Compone nt Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadingsa Total % of VarianceCumulative % Total % of Variance Cumulative % Total 1 3.922 20.644 20.644 3.922 20.644 20.644 3.348 2 3.076 16.191 36.835 3.076 16.191 36.835 2.979 3 2.438 12.834 49.669 2.438 12.834 49.669 2.973 4 1.912 10.064 59.733 1.912 10.064 59.733 1.832 5 1.212 6.380 66.112 1.212 6.380 66.112 1.586 6 1.185 6.234 72.347 1.185 6.234 72.347 1.966 7 .958 5.044 77.390 8 .763 4.017 81.407 9 .625 3.290 84.698 10 .541 2.847 87.544 11 .480 2.525 90.070 12 .462 2.429 92.499 13 .390 2.055 94.554 14 .318 1.673 96.227 15 .199 1.048 97.275 16 .169 .890 98.166 17 .160 .843

Financial Statements based on FVA are more transparent than those prepared using HCA 1.000 .708 Q26. FVA will enhance transparency for comparability. 1.000 .738 Q27. FVA limits the company’s ability to manipulate their net income. 1.000 .666 Q28. FVA method is a complex method for financial reporting. 1.000 .724 Extraction Method: Principal Component Analysis. Conclusion: In the above table if the extraction value is more one can say that most of the respondents are agreeing with that factor. Table-5.4 Total Variance Explained Compone nt Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadingsa Total % of VarianceCumulative % Total % of Variance Cumulative % Total 1 3.922 20.644 20.644 3.922 20.644 20.644 3.348 2 3.076 16.191 36.835 3.076 16.191 36.835 2.979 3 2.438 12.834 49.669 2.438 12.834 49.669 2.973 4 1.912 10.064 59.733 1.912 10.064 59.733 1.832 5 1.212 6.380 66.112 1.212 6.380 66.112 1.586 6 1.185 6.234 72.347 1.185 6.234 72.347 1.966 7 .958 5.044 77.390 8 .763 4.017 81.407 9 .625 3.290 84.698 10 .541 2.847 87.544 11 .480 2.525 90.070 12 .462 2.429 92.499 13 .390 2.055 94.554 14 .318 1.673 96.227 15 .199 1.048 97.275 16 .169 .890 98.166 17 .160 .843

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